{"id":"W4287773581","doi":"10.1021/acsami.0c15612.s001","title":"Electrospun nanodiamond-silk fibroin membranes: a multifunctional\\n platform for biosensing and wound healing applications","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Diamond and Carbon-based Materials Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"RMIT University; ARC Centre for Nanoscale BioPhotonics; Ontario Ministry of Natural Resources and Forestry; South Australian Health and Medical Research Institute; Australian National Fabrication Facility","keywords":"Nanodiamond; Membrane; Fibroin; SILK; Materials science; Electrospinning; Wound healing; Nanofiber; Biocompatibility; Biomedical engineering; Nanotechnology; Nanoscopic scale; Fluorescence; Composite material; Chemistry; Polymer; Medicine; Surgery","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009695708,0.0002643278,0.00007025749,0.0001752386,0.0001236319,0.0001672202,0.0001259329,0.00033608,0.0005238423],"category_scores_gemma":[0.00005969532,0.00009541045,0.0001154036,0.00007562032,0.00008654982,0.0002381052,0.0001353995,0.0001735157,0.0001854631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000188611,"about_ca_system_score_gemma":0.00009444676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001870306,"about_ca_topic_score_gemma":0.0006197805,"domain_scores_codex":[0.999953,0.000004505746,0.00000302681,0.00001331691,0.00001903078,0.000007075714],"domain_scores_gemma":[0.9999638,0.000004945886,0.00001462213,0.00000346204,0.000005902393,0.000007189692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005398587,0.000005304539,0.00002141206,0.00001445215,8.746511e-7,0.00001626874,0.000003143426,0.00003421102,0.9988127,0.00005305538,0.00001623568,0.001017038],"study_design_scores_gemma":[0.000003617365,0.00006465679,0.000624709,0.000002872889,0.000002941255,0.00008512011,0.000006987897,0.001092639,0.995945,0.00003206429,0.002136192,0.000003256555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659323,0.003247369,0.02589018,0.0002151389,0.00007030155,0.00006449731,0.0002000101,0.0002325534,0.004147598],"genre_scores_gemma":[0.9742989,0.001367438,0.01889069,0.00006952329,0.00001734152,0.00003778395,0.0001808164,0.00002024637,0.00511728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005238423,"threshold_uncertainty_score":0.001752377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07552395185433355,"score_gpt":0.2245413674469838,"score_spread":0.1490174155926502,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}